- Most up-to-date publication on Interactive computing with IPython 4.0;
- Detailed, example-rich advisor that permits you to use the main complex point interactive programming with IPython;
- Get versatile interactive programming with IPython utilizing this complete guide
IPython is an interactive computational atmosphere during which you could mix code execution, wealthy textual content, arithmetic, plots, and wealthy media.
This booklet gets IPython builders brand new with the newest developments in IPython and dive deep into interactive computing with IPython. This a complicated advisor on interactive and parallel computing with IPython will discover complicated visualizations and high-performance computing with IPython in detail.
You will speedy brush up your wisdom of IPython kernels and wrapper kernels, then we are going to flow to complicated suggestions similar to trying out, Sphinx, JS occasions, interactive paintings, and the ZMQ cluster. The ebook will disguise issues akin to IPython Console Lexer, complex configuration, and third-party tools.
By the tip of this booklet, it is possible for you to to exploit IPython for interactive and parallel computing in a high-performance computing environment.
What you'll learn
- Develop talents to take advantage of IPython for prime functionality computing (HPC)
- Understand the IPython interactive shell
- Use XeroMQ and MPI to cross messages
- Visualize the data
- Acquire wisdom to check and record the data
- Get to grips with the new advancements within the Jupyter computing device system
About the Author
Thomas Bitterman has a PhD from Louisiana kingdom collage and is presently an assistant professor at Wittenberg collage. He formerly labored within the for a few years, together with a up to date stint on the Ohio Supercomputer middle. Thomas has event in such varied parts as digital trade, firm messaging, instant networking, supercomputing, and academia. He additionally loves to hold sharp, writing fabric for Packt Publishing and O'Reilly in his copious loose time.
Table of Contents
- Using IPython for HPC
- Advanced Shell Topics
- Stepping as much as IPython for Parallel Computing
- Messaging with ZeroMQ and MPI
- Opening the Toolkit – The IPython API
- Works good with Others – IPython and Third-Party Tools
- Seeing Is Believing– Visualization
- But It labored within the Demo! – Testing
- Visiting Jupyter
- Into the Future
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